Extensive Capabilities Research Articles

Computer-Assisted Simulations Using R and RStudio to Assist in Operations Research and Analysis in the Context of Clinical Laboratory Management

Operations research (OR) is a valuable yet underutilized field in clinical laboratory management, offering practical solutions to optimize workflows, resource allocation, and decision-making. Despite its potential, the adoption of OR methodologies remain limited due to a lack of training and familiarity among pathologists and laboratory professionals. This paper addresses this gap by presenting an accessible introduction and practical guide to analyzing operations research problems in clinical laboratories using computer-assisted simulations in R, implemented within the R Studio environment. The proposed framework emphasizes simplicity and flexibility, leveraging the extensive capabilities of base R to model and analyze critical OR questions. The paper outlines step-by-step methods for defining problems, constructing simulation models, and interpreting results, ensuring that readers can replicate and adapt these techniques to their unique laboratory contexts. Key features of the framework include its emphasis on reproducibility, customization, and the integration of data-driven insights into decision-making processes. Case studies and examples drawn from real-world laboratory scenarios illustrate the application of R simulations to address challenges such as minimizing turnaround times, balancing staffing levels, and managing inventory efficiently. This guide aims to empower laboratory professionals and pathologists with the tools and skills to integrate operations research into their practice, fostering a culture of innovation and efficiency in clinical settings. By bridging the gap between OR theory and practical application, this paper contributes to the broader adoption of computational approaches in laboratory management, ultimately enhancing the quality and sustainability of healthcare services.

Representation of spatial information in the CA1 field

Information in the brain is encoded by large populations of neurons – neural ensembles. The place cells in the hippocampal CA1 field have become an experimental model for the study of neural ensembles of the brain due to the convenience of research. This review is devoted to the latest studies of place cells in the CA1 field. We consider the principles of encoding space by place cells, mechanisms for controlling the activity of place cells, anatomical and physiological features of place cells in different parts of the CA1 field. Key points: 1. There are rate and phase coding; 2. Dense local connections between pyramidal neurons can provide information processing; 3. Interneurons are involved in the formation of both the rate and phase code of place cells; 4. Pyramidal neurons are anatomically and functionally divided into deep and superficial; 5. Along the dorsoventral axis, the spatial and non-spatial component of information is generalized. The CA1 field has extensive capabilities for signal processing and can implement a computationally complex operation in the cognitive processes of the brain.

Dog sniffing biomechanic responses in an odor detection test of odorants with differing physical properties.

Dogs are utilized in forensic science for their extensive scent detection capabilities. They are often considered the "gold standard" in field detection for targets such as illicit drugs and explosives. Despite their prevalence in the field, relatively little is known about how dogs interact with and transport volatile organic compounds through their olfactory system. In this study, two groups of dogs were utilized - Sport detection dogs (n=19) that participate in the National Association of Canine Scent Work and have achieved advanced standing through training and successful search competitions and law enforcement explosive detection dogs (n=8) which were included for comparison. Both groups were presented with two target odorants having differing molecular properties, 2-ethyl-1-hexanol and ammonia, two non-target odorants, 1-bromooctane and methyl benzoate, and a negative control. Canines were tested prior to experience with the target odorants, when all odorants were novel, after some brief training with the target odorants, and after longer training time with the target odorants. The non-target odorants were never used in training. Sniffing was measured using flow sensors embedded in a wall immediately in front of the odorants held in a closed cylinder. Sensor data was used to calculate sniff flow rate, frequency (sniffs per seconds) and volume. Results indicated no difference in sniffing dynamics between target odorants; however, sniffing frequency increased significantly with increased experience with the target odorants (Wilcoxon rank sum exact test, W= 148, p=6×10-5). Sniff volume and flow rate showed a positive correlation to body mass for all sport detection dogs (slope = 2.71, F(1,17)= 9.48, p= 0.007, R2= 0.32), though the R2 was low, indicating other factors at play. Law enforcement detection dogs were shown to take in significantly higher mean total sniff volumes (Wilcoxon rank sum exact test: W= 7, p=10-4) and volume flow rates (Wilcoxon rank sum exact test: W= 5, p=6×10-5) compared to the sport detection dogs, but the sniff frequency remained similar for both groups.

Three-dimensional numerical calculation and case application of IP five-directional well logging

Abstract Conventional well logging can effectively detect the vertical distribution range of ore bodies near the well by placing detectors in the well. However, its detection capability for the horizontal extension of ore bodies is limited. Therefore, starting from the differential equations satisfied by the point source in three-dimensional structures, this paper deduced the variational problem satisfied by the total potential under three-dimensional complex conditions. By focusing on well logging, tetrahedral cross-grid partitioning technology was employed to achieve high-precision three-dimensional finite element forward modeling. Simulations were carried out for different forms of ore bodies using the induced polarization five-direction observation method, considering the presence of ore bodies near the well and the case where the measurement well passes through the ore body. The paper analyzed and summarized the induced polarization anomaly patterns formed by ore bodies with low resistance and high polarization in different horizontal extension directions under induced polarization five-direction logging with power supply measurements from different directions. Based on this, a human-computer interaction system was constructed to perform forward fitting and inversion interpretation of the measured induced polarization data, resulting in a good application effect.

Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics.

Inspired by the extensive signal processing capabilities of the human nervous system, neuromorphic artificial sensory systems have emerged as a pivotal technology in advancing brain-like computing for applications in humanoid robotics, prosthetics, and wearable technologies. These systems mimic the functionalities of the central and peripheral nervous systems through the integration of sensory synaptic devices and neural network algorithms, enabling external stimuli to be converted into actionable electrical signals. This review delves into the intricate relationship between synaptic device technologies and neural network processing algorithms, highlighting their mutual influence on artificial intelligence capabilities. This study explores the latest advancements in artificial synaptic properties triggered by various stimuli, including optical, auditory, mechanical, and chemical inputs, and their subsequent processing through artificial neural networks for applications in image recognition and multimodal pattern recognition. The discussion extends to the emulation of biological perception via artificial synapses and concludes with future perspectives and challenges in neuromorphic system development, emphasizing the need for a deeper understanding of neural network processing to innovate and refine these complex systems.

Ultrasmall Black Phosphorus Quantum Dots with Robust Antioxidative Properties for Acute Kidney and Liver Injury Therapy.

Acute organ injuries, such as acute kidney injury (AKI) and acute liver injury (ALI), usually present high morbidity and mortality in patients. However, the current clinical treatments remain limited, especially the lack of effective drug-based treatment. Since these acute injuries are often associated with reactive oxygen species (ROS) overproduction, it is a promising strategy to develop therapeutic agents with potent ROS scavenging ability and excellent biocompatibility for efficient antioxidation therapy. Black phosphorus quantum dots (BPQDs), low-dimensional nanomaterials prepared through a straightforward one-step method and capable of complete controllable biodegradation, offer significant potential. This study comprehensively explores the extensive free-radical scavenging capabilities of BPQDs, underscoring their immense potential in treating ROS-related organ injuries. BPQDs could simultaneously achieve radical scavenging of DPPH, ABTS·, OH·, and O2 -· and exhibit excellent cytoprotective effects against ROS-mediated damage even at extremely low dosages. Besides, the ultrasmall size of BPQDs (≈3-5nm) allows them to effectively penetrate the glomerular filtration barrier (≈6nm), significantly improving the symptoms of AKI and ALI in vivo. The therapeutic efficacy and great biocompatibility of BPQDs facilitate the clinical management of ROS-related diseases, which will broaden the applications of QDs in the field of biomedicine.

Nanoconjugate Carrying pH-Responsive Transferrin Receptor-Targeted Hesperetin Triggers Triple-Negative Breast Cancer Cell Death through Oxidative Attack and Assemblage of Pro-Apoptotic Proteins.

Triple-negative breast cancer (TNBC) is recognized as a major aggressive subtype of breast cancer due to its expeditious worsening growth, extensive metastatic capability, and recalcitrance to standard current treatments. Hesperetin (HSP), a natural bioflavonoid from citrus fruits, demonstrates pronounced anticancer efficacy, but its hydrophobicity limits its clinical development. The present study reports the fabrication of a biocompatible and pH-responsive transferrin (TF) receptor-targeted HSP-loaded poly(lactic-co-glycolic acid) (PLGA) nanobioconjugate (PLGA-HSP-TF NPs) and the exploration of its in vitro and in vivo antineoplastic potential. PLGA nanoparticles (NPs), PLGA-HSP NPs, and PLGA-HSP-TF NPs were synthesized and characterized by DLS, FTIR, FE-SEM, and 1H NMR spectroscopy. The stability and in vitro release profile of nanoparticles were inspected, and anticancer efficacy was scrutinized in terms of in vitro cytotoxicity, oxidative stress and apoptosis biomarkers, and cell cycle arrest. In vivo tumor regression and host survival studies were executed in Ehrlich ascites carcinoma (EAC) cell-bearing Swiss albino mice. The drug uptake of highly stable PLGA-HSP-TF NPs was accomplished effectively in MDA-MB-231 cells and showed the pH-dependent intracellular release of HSP, which generated excessive intracellular reactive oxygen species (ROS) that led to oxidative assault to the TNBC cells. This elevated ROS dropped the mitochondrial membrane potential and triggered apoptosis-mediated cell death by arresting the cell cycle at the G0/G1 phase. Furthermore, PLGA-HSP-TF NPs unveiled significant in vivo Ehrlich ascites carcinoma regression and host survival compared to free HSP with minimum toxicity at a minimum dose of 20 mg/kg body weight. The study divulges that PLGA-HSP-TF NPs may be an astounding anticancer nanocandidate for aggressive triple-negative breast cancer therapy.

Efficient I/O Performance-Focused Scheduling in High-Performance Computing

High-performance computing (HPC) systems are becoming increasingly important as contemporary exascale applications with demand extensive computational and data processing capability. To optimize these systems, efficient scheduling of HPC applications is important. In particular, because I/O is a shared resource among applications and is becoming more important due to the emergence of big data, it is possible to improve performance by considering the architecture of HPC systems and scheduling jobs based on I/O resource requirements. In this paper, we propose a scheduling scheme that prioritizes HPC applications based on their I/O requirements. To accomplish this, our scheme analyzes the IOPS of scheduled applications by examining their execution history. Then, it schedules the applications at pre-configured intervals based on their expected IOPS to maximize the available IOPS across the entire system. Compared to the existing first-come first-served (FCFS) algorithm, experimental results using real-world HPC log data show that our scheme reduces total execution time by 305 h and decreases costs by USD 53 when scheduling 10,000 jobs utilizing public cloud resources.

Insulator-donor electron wavefunction coupling in pseudo-bilayer organic solar cells achieving a certificated efficiency of 19.18%

Abstract The incorporation of polymeric insulators has led to notable achievements in the field of organic semiconductors. By altering the blending concentration, polymeric insulators exhibit extensive capabilities in regulating molecular configuration, film crystallinity, and mitigation of defect states. However, current research suggests that the improvement in such physical properties is primarily attributed to the enhancement of thin film morphology, an outcome that seems to be an inevitable consequence of incorporating insulators. Herein, we report a general and completely new effect of polymeric insulators in organic semiconductors: the insulator-donor electron wavefunction coupling effect. Such insulators can couple with donor polymers to reduce the energy barrier level and facilitate the intramolecular electron transport. Besides the morphological effects, we observed that this coupling effect is another mechanism that can significantly enhance the electron mobility (up to 100 times) through the incorporation of polymeric insulators in a series of donor systems. With this effect, we proposed a polymeric insulator blending approach to fabricate state-of-the-art pseudo-bilayer organic solar cells, and the PM6/L8-BO device exhibits a high efficiency of 19.50% (certificated 19.18%) with the improved interfacial electron transport property. This work not only offers a novel perspective on the quantum effect of polymeric insulators in organic semiconductors, but also presents a simple yet effective method for enhancing the performance of organic solar cells.

High-Performance Flexible PLA/BTO-Based Pressure Sensor for Motion Monitoring and Human-Computer Interaction.

Flexible electronics show wide application prospects in electronic skin, health monitoring, and human-machine interfacing. As an essential part of flexible electronics, flexible pressure sensors have become a compelling subject of academic research. There is an urgent need to develop piezoelectric sensors with high sensitivity and stability. In this work, the high flexibility of polylactic acid (PLA) film and the excellent ferroelectric properties and high dielectric constant of tetragonal barium titanate (BTO) led to their use as filling materials to fabricate flexible piezoelectric composite films by spinning coating. PLA is used to produce flexible binding substrates, and BTO is added to the composite to enhance its electrical output by improving its piezoelectric performance. The peak output voltage of the PLA/BTO tetragonal piezoelectric film is 22.57 V, and the maximum short-circuit current was 3041 nA. Durability tests showed that during 40,000 s of continuous operation, in the range of 15~120 kPa, the linear relationship between pressure and the film was excellent, the sensitivity for the output voltage is 0.176 V/kPa, and the output current is 27.77 nA/kPa. The piezoelectric pressure sensor (PPS) also enables accurate motion detection, and the extensive capabilities of the PENG highlight its potential in advancing motion sensing and human-computer interactions.

Job Scheduling in Hybrid Clouds With Privacy Constraints: A Deep Reinforcement Learning Approach

ABSTRACTWith the proliferation of cloud computing and the escalating demand for extensive data processing capabilities, an increasing number of enterprises are embracing hybrid cloud solutions. However, as more businesses move toward hybrid clouds, the need for effective solutions to privacy and security concerns becomes increasingly important. Although current scheduling approaches for cloud computing have addressed privacy protection to some extent, few have adequately considered the unique challenges posed by hybrid clouds. To address this gap, we propose a novel approach for scheduling jobs in hybrid clouds that prioritizes privacy protection. Our approach, called PH‐DRL, leverages Deep Reinforcement Learning (DRL) to intelligently allocate jobs to virtual machines, optimizing both privacy and Quality of Service (QoS), while minimizing response time. We present the detailed implementation of our approach and our experimental results demonstrate the superior performance of PH‐DRL in terms of privacy protection compared to existing methods.

An alternative instrumental method for studying the morphofunctional state of eyelids in chronic blepharitis

Background: To date, the assessment of morphofunctional changes within eyelids is performed using laser scanning confocal microscopy, which has extensive diagnostic capabilities. Identification of the indicators equivalence of this method and laser Doppler flowmetry will confirm the existence of an alternative, objective and economical method of eyelid examination in chronic blepharitis. Aim: To prove the possibility of laser Doppler flowmetry application as an alternative method of eyelid morphofunctional state assessment. Materials and methods: The study included 62 patients (124 eyes) with an established diagnosis of chronic mixed demodecticosis blepharitis, including 46 women and 16 men, mean age 65.8 ± 3.2 years, randomly assigned into two groups with identical age and gender composition. Group 1 patients (31 patients, 62 eyes) were treated with cosmeceuticals containing terpenes and terpenoids 2 times a day and tear substitute 3 times a day for 1.5 months. Group 2 patients (31 patients, 62 eyes) used an eyelid care gel containing sulphur medicaments 2 times a day and a tear substitute 3 times a day for 1.5 months. In addition to standard ophthalmological examination, laser Doppler flowmetry and laser scanning confocal microscopy were performed. Dynamic follow-up was performed after 1.5 and 3 months. Results: The analysis of laser scanning confocal microscopy and laser Doppler flowmetry parameters revealed a high inverse correlation between the density of inflammatory cells of the eyelids tarsal conjunctiva and neurogenic oscillations of blood flow, as well as high direct correlation with the index of blood flow shunting. A marked direct correlation between the density index of meibomian gland acinuses and the parameters of myogenic oscillations of blood flow and neurogenic oscillations of lymph flow was established. Conclusions: Pearson’s correlation analysis performed on laser scanning confocal microscopy and laser Doppler flowmetry parameters assessing the morphofunctional state of the eyelids demonstrated the presence of equivalence in both study groups with high statistical reliability. The obtained data confirm the possibility of using laser Doppler flowmetry method for objective assessment of eyelid condition and allow the parameters of this method to serve as criteria for choosing pathogenetically oriented therapy of chronic blepharitis with evaluation of its effectiveness.

Comparison of Gait in Women with Degenerative Changes of the Hip Joint and Healthy Women Using the MoKA System-A Pilot Study.

Osteoarthritis (OA) is a global problem. There are few reports in the literature regarding the temporal and spatial parameters of gait in people with OA. The aim of this study was to determine spatiotemporal parameters for the pelvis and lower limbs during walking in women with OA and to compare these parameters with healthy people. For this purpose, a 6 min walking test (6MWT) was carried out. OA subjects had worse outcomes compared to the control group (p < 0.05). Data were collected using IMU sensors integrated into the MoKA system and mounted on indicator points on the body. Limited mobility of the pelvis in the frontal plane was observed in the study group, which influenced walking strategy. For the comparison with the control group at each minute, p < 0.05. IMU sensors attached to the body and integrated in one application provide extensive research and diagnostic capabilities.

Augmented Reality Technology (ART) in Science Education and Engineering Technology: A Review

Abstract : This paper provides a comprehensive analysis of Augmented Reality Technology (ART) in Science Education and Engineering Technology. Science Education and Engineering Technology go hand in hand as without scientific studies applications cannot exist. The term science is well known for knowledge-based society. It has a vast scope in this world. In every step of human life, the terms Science and Technology are both the two sides of one coin. The main objectives of this review are to - 1. Understand the concept of Augmented Reality Technology (ART). 2. Identify the different types of Augmented Reality Technology (ART). 3. Find out the correlation between Augmented Reality Technology (ART) and Science Education. 4. Identify the various strategies of Augmented Reality Technology (ART) for Science Education. The rising prominence of Augmented Reality (AR) technology stems from its ability to deliver captivating and interactive experiences to users. The current landscape of AR technology is characterized by its dynamic and fast-paced evolution, with numerous applications emerging across industries like gaming, retail, education, and healthcare. By overlaying digital content onto the physical world, AR technology creates a blended reality environment that offers engaging and immersive experiences to users. In particular, AR has the potential to revolutionize the methods through which students comprehend and interact with scientific and engineering concepts. It presents an opportunity for future research to delve deeper into exploring the extensive capabilities of this technology and unlock its full potential in educational contexts. Keywords : Augmented Reality Technology (ART); Education; Engineering; Science Education; Technology.

Analysis of User Interfaces for Ground Control Stations of Unmanned Aerial Vehicles

Introduction. In the modern world, software (SW) is updated daily, particularly for ground control stations (GCS) of unmanned aerial vehicles (UAVs). These systems ' user interfaces (UI) ensure operator interaction with the drone, flight control, mission planning, and realtime data acquisition. These interfaces must be functional, convenient, and intuitive, allowing operators to perform their tasks effectively. Examining global experience allows for an evaluation of existing systems and the identification of areas for improvement. Important aspects include creating intuitive UIs to prevent information overload, ensuring situational awareness, adapting to extreme conditions, and integrating with other systems. The use of virtual and augmented reality technologies, as well as artificial intelligence, can enhance the functionality and convenience of GCS. Such analysis will help in creating safe, efficient, and reliable systems for UAV control. The purpose of the paper is to investigate and conduct a comprehensive analysis of existing user interfaces of software for UAV ground control stations, focusing on their functional capabilities and ease of use. Methods. The following methodological tools were used: concepts of intellectualization of information technologies, the theory of intelligent control, the methodology of building autonomous systems, decision-making theory, and artificial intelligence theory. Results. A review of global experience in user interface development was conducted. The UIs of each of the studied software were analyzed, and their functional capabilities were assessed, identifying their strengths and weaknesses. Comparative tables of interface products were compiled based on their functional capabilities and UI usability levels. Generalized recommendations were prepared for creating a unified interface that combines the best features of existing solutions and addresses their shortcomings. Conclusions. The analysis of GCS UI design for UAVs showed that all systems have strengths and weaknesses. The UI of the Mission Planner software has the most extensive capabilities, but it also requires improvement. Future development should add roles for military pilots and operators, develop a more intuitive and user-friendly interface that meets user needs, and simplify SW settings. For working in extreme conditions, the interface needs to be optimized. Enhancements in data visualization will help make information clear and easy to understand, which is critically important in fast-paced and dangerous situations. Keywords: user interface, ground control station, UAV, virtual reality, augmented reality.

Technological and Mechanical Studies on Additively Manufactured Cellular Structures Made of the Ultrafuse 316L Composite Filament

Regular cellular materials produced using additive manufacturing (AM) techniques represent a significant development trend in modern engineering materials. Depending on the applied elementary unit cell of topology, it is possible to define the course of the structure deformation process in order to obtain the highest possible energy absorption effectiveness. This feature makes regular cellular structural materials particularly attractive for a number of industrial branches. This paper presents the results of technological trials and the results of experimental studies on the mechanical properties of regular cellular structures made using 3D printing technology under compression test loading conditions. The material used for their production was the Ultrafuse 316L filament and the fused filament fabrication (FFF) technique. The proposed material is a polymer-metal composite with a manufacturing process similar to metal injection moulding (MIM). The adopted research methodology included a feasibility study aimed at achieving material homogeneity and compression tests of the developed and manufactured regular cellular structures under quasi-static loading conditions. Several structural topologies were analysed. Experimental results indicated that regular cellular structures made from 316L steel exhibit high mechanical strength and extensive plastic deformation capabilities. The utilized in this work manufacturing technology used combines the advantages of 3D printing process with the potential of powder metallurgy. The proposed technique of structure manufacturing process is much cheaper than other based on melting metallic powders.

EBWO‐GE: An innovative approach to dynamic VM consolidation for cloud data centers

SummaryCloud data centers (CDCs) have revolutionized global computing by offering extensive storage and processing capabilities. Nevertheless, the environmental impact of these processes, including their substantial energy consumption and carbon emissions, calls for implementing more efficient techniques. Efficient virtual machine (VM) consolidation is crucial in optimizing resource utilization and reducing energy consumption. Current methods for enhancing energy efficiency often lead to issues such as service level agreements (SLAs) violations and quality of services (QoS) degradation. This study presents a novel approach to host selection using a grey‐extreme (GE) machine learning model, which accurately predicts over and underutilized hosts. In addition, a VM placement technique called enhanced black widow optimization (EBWO) utilizes black widow optimization heuristic techniques and a differential evolutionary approach to optimize VM placement. The proposed dynamic VM consolidation technique optimizes energy utilization while meeting strict SLA requirements and enhancing QoS metrics in CDCs. Extensive analyses were conducted using the Cloudsim toolkit to validate the approach's effectiveness. These analyses encompassed conditions such as random workloads in heterogeneous environments. The simulation results showed that GE‐EBWO outperforms other techniques and improves energy efficiency by 12%–15%. In addition, it significantly decreases VM migrations by 11%–14% compared to other advanced methods. The study validates the practicality of the proposed technique in moving towards environmentally friendly CDCs.

Encoding innate ability through a genomic bottleneck

Animals are born with extensive innate behavioral capabilities, which arise from neural circuits encoded in the genome. However, the information capacity of the genome is orders of magnitude smaller than that needed to specify the connectivity of an arbitrary brain circuit, indicating that the rules encoding circuit formation must fit through a "genomic bottleneck" as they pass from one generation to the next. Here, we formulate the problem of innate behavioral capacity in the context of artificial neural networks in terms of lossy compression of the weight matrix. We find that several standard network architectures can be compressed by several orders of magnitude, yielding pretraining performance that can approach that of the fully trained network. Interestingly, for complex but not for simple test problems, the genomic bottleneck algorithm also captures essential features of the circuit, leading to enhanced transfer learning to novel tasks and datasets. Our results suggest that compressing a neural circuit through the genomic bottleneck serves as a regularizer, enabling evolution to select simple circuits that can be readily adapted to important real-world tasks. The genomic bottleneck also suggests how innate priors can complement conventional approaches to learning in designing algorithms for AI.

An Improved YOLOv8 OBB Model for Ship Detection through Stable Diffusion Data Augmentation.

Unmanned aerial vehicles (UAVs) with cameras offer extensive monitoring capabilities and exceptional maneuverability, making them ideal for real-time ship detection and effective ship management. However, ship detection by camera-equipped UAVs faces challenges when it comes to multi-viewpoints, multi-scales, environmental variability, and dataset scarcity. To overcome these challenges, we proposed a data augmentation method based on stable diffusion to generate new images for expanding the dataset. Additionally, we improve the YOLOv8n OBB model by incorporating the BiFPN structure and EMA module, enhancing its ability to detect multi-viewpoint and multi-scale ship instances. Through multiple comparative experiments, we evaluated the effectiveness of our proposed data augmentation method and the improved model. The results indicated that our proposed data augmentation method is effective for low-volume datasets with complex object features. The YOLOv8n-BiFPN-EMA OBB model we proposed performed well in detecting multi-viewpoint and multi-scale ship instances, achieving the mAP (@0.5) of 92.3%, the mAP (@0.5:0.95) of 77.5%, a reduction of 0.8 million in model parameters, and a detection speed that satisfies real-time ship detection requirements.

The mechanics of male courtship display behaviour in the Ptiloris riflebirds (Aves: Paradisaeidae)

Abstract Sexual selection through female choice has driven the evolution of some of the most elaborate signalling behaviours in animals. These displays often require specialized morphological adaptations and may incorporate signals in multiple sensory modalities. Visual and acoustic signals are often precisely choreographed in temporally structured courtship performances, though the precise mechanics of such signalling behaviours are often enigmatic. We find that riflebirds (genus Ptiloris)—a bird of paradise clade—achieve their remarkable display postures by hyperextending the wrist joint, vastly exceeding the maximal wrist extension capabilities of any other known bird. Using video collected in the field, we then show that this hypermobility is required for a sonation unique to riflebirds, and find that the yellow interior of the mouth is displayed in the dynamic phase of display. As this sonation cannot be produced when the mouth is exposed, it represents a mechanical constraint to signal design. Finally, we used a large morphometric dataset to describe patterns of sexual dimorphism in wing length across diverse bird of paradise species, and find evidence of sexual selection for large and structurally modified wings used in riflebird displays. Our study highlights nuanced choreographic differences in the display behaviours of different riflebird species, and sheds light on the intricate design features of sexual signals in this fascinating taxon.